Optical coherence tomography (OCT) is an imaging modality for high-resolution, depth-resolved cross-sectional and 3-dimensional (3D) imaging of internal structures in biological tissue. OCT relies on the principle of low-coherence interferometry to measure light back-reflected from tissue structures at different depths. This means that the beam sampling the tissue interferes at the detector with a reference beam that travels the same distance and is back-reflected from a mirror. To obtain an OCT image, the instrument scans a light beam laterally, creating a series of axial scans (A-lines) that contains information on the strength of reflected signal as a function of depth. The combination of successive A-lines acquired at one lateral position (known as a B-scan) allows the visualization of a 2-dimensional section of the tissue anatomy, henceforth referred here as the cross-sectional image. Among its many applications, ocular imaging has found an extensive clinical use in the past years, both for the anterior (cornea and iris) and posterior (retina) sections.
Initially, imaging by OCT required a moving reference mirror to produce a depth-resolved reflectivity profile of the tissue under investigation. This modality is known as time-domain OCT. An alternative modality known as Fourier-domain OCT (FD-OCT) that uses a stationary reference mirror was later introduced. FD-OCT achieves depth-resolved imaging by separately measuring the interference of the spectral components of a broadband light source. This can be accomplished by either an incident broadband pulse of light that is later separated into its spectral components by a spectrometer or alternatively, by scanning the spectrum of a high-speed swept-source and measuring the interference signal with balanced photodetectors. With the advent of FD OCT, the allowed scanning speed increased tremendously and the potential for functional imaging (such as imaging vascular networks) could be realized.
Optical coherence tomography angiography (OCTA) is a noninvasive blood flow imaging technique based on OCT that allows depth-resolved visualization of vascular maps with capillary resolution. Flow detection using OCT was first demonstrated by Doppler OCT, a technique that images blood flow by evaluating phase differences between adjacent depth profiles. More recent OCTA algorithms on the other hand, rely on mathematical operations (e.g. decorrelation, variance, difference, or ratio) that quantify variations in the phase and/or amplitude of OCT signal between at least two consecutive B-scans acquired at the same raster position. For example, the speckle variance method computes the amplitude decorrelation between consecutive cross-sectional OCT images to identify variations in the intensity of the OCT signal due to the motion of blood cells. An improved version of the speckle variance method is the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm, which splits the interferogram before computing the amplitude decorrelation and later averages the flow images generated by all spectral splits, enhancing the signal-to-noise ratio. SSADA uses only two B-scans at each lateral position, which is beneficial for a reduced scanning time. Another OCTA method referred to as split-spectrum amplitude and phase-gradient angiography (SSAPGA) exploits the phase of the OCT signal besides the amplitude to further improve the flow image quality. Yet another alternative that utilizes the complex OCT signal is known as optical microangiography and relies on a modified Hilbert transform to distinguish moving scatterers from static scatterers. All of these modalities have one common purpose, to exploit the larger variation in OCT signal between scans due to moving scatterers in order to represent the pixels corresponding to blood vessels brighter than the pixels representing the surrounding tissue.
Bulk motion of the eye generates variation in OCT signal that can be detected with the various OCTA algorithms. Currently, correction of bulk motion contribution to flow signal in OCTA is performed by an algorithm that subtracts the median decorrelation value of the retinal section of each B-frame.